**2.1 Dairy sector and biogas use in Rungwe district**

Rungwe district lies between latitudes 8030 E and 9030 E and longitudes 330S and 340 S. It is one of the six districts of Mbeya Region, located in the Southern Highlands of Tanzania. The other districts are Kyela, Chunya, Ileje, Mbeya Rural and Mbozi. Rungwe district has a total area of 2211 sq. km of which 75% is arable land (URT, 1997). Of the remaining area, 44.5 sq. km is covered by forest while 498.3 sq. km is either mountainous or residential areas.

The district is one of the densely populated districts in Tanzania (URT, 2002) with a population of 307,270, which is equivalent to 139 persons per square kilometre with an annual growth rate of 0.9% (URT 2010). The district has limited natural vegetation which varies from upper montane forest at higher elevations to the wet woodland (Miombo) at lower elevations. Forestry reserve accounts for 43,749.9 ha and other forests about 65,813 ha (URT, 2008). In recent years, much of this natural vegetation has been cleared/transformed for agriculture, for habitation, and firewood. Most of the remaining natural vegetation is found in government forest reserves and in locally protected areas, though even these areas have been subjected to varying degrees of people driven disturbances.

Rungwe district put great importance to livestock development particularly dairy cattle as one of the major economic activities. In 2005 the district had 26,137 indoor fed dairy cattle with milk production estimated to be 41,000,000 litres per year. The district has 74,450 households and almost half of the households keep some cattle or pigs in their homestead with an average of between 2-6 cattle (Mwakaje, 2008). Smallholder dairy production is an important undertaking and, if adequately supported by appropriate policies and adaptive research technologies, it may contribute significantly towards the household economy, selfsufficiency in milk and national gross domestic product (Swai and Kimambo, 2011). Walshe et al (1991) comments that where there is access to a market, dairying is preferred to meat production since it makes more efficient use of feed resources and provides a regular income to the producer.

Promotion of smallholder dairy farming can solve the problem of rural poor accessing to clean energy like biogas.

Dairy Farming and the Stagnated Biogas

Use in Rungwe District, Tanzania: An Investigation of the Constraining Factors 315

understanding their performance and constraining factors they are facing. Primary data were collected in areas related to investment cost, awareness, household energy demand, technology service providers, and expertise. In addition, there were consultations with service providers to get information on cost, demand as well as factors constraining the spread of the biogas technology in the District. Furthermore, there was a consultation with local and district institutions and authorities for detailed information on biogas use in the

The sample frame for this study involved respondents with dairy cattle/biogas use and those with dairy cattle but have not installed biogas plants. Also respondents with access to electricity and other clean energy sources such as LPG were included in the sample. A total of 3 villages were selected for the household sample. These were *Isagilo*, *Kyimo* and *Mpandapanda*. The selection of the villages based on the availability of dairy cows, adoption of biogas technology, availability of other energy sources, socio-economic status and accessibility. The households were selected purposively for those with biogas as well as those with access to electricity as they are few but random for the rest of the dairy keepers. The total number of households (n) to be surveyed was estimated using the formula below:

> 2 N

<sup>=</sup> <sup>+</sup> (1)

1 Ne

A sample size of about 10% was selected making a total sample of 120 households. Out of this, 35 had biogas facilities and the remaining 85 had dairy cattle without biogas facility (Table 1). Village roster were used to select the sample households. Data were collected using structured and semi-structured questionnaires and analysed using Statistical Package for Social Sciences (SPSS) as well as livelihoods models. Results have been presented in

biogas

Total 42 35 85 120

HH with biogas selected for interview

22 19 25 43

13 11 22 30

7 5 22 27

HH without biogas selected for interview

Total Sample selected

district and whether there has been any efforts to facilitate the adoption of biogas.

n

N = total number of households in the village; and

Where: n = sample size between 5 and 10%

e = desired margin of error.

Village Characteristics HH With

Biogas project started free of charge in 1996 and 12 HH installed biogas plants

Large population of dairy cows and have electricity

Large population of dairy cattle but limited number of

Table 1. Village Characteristics and Sample Size (households)

services

biogas users.

tables and figures.

Isagilo

Kyimo

Mpandapanda

The district is also famous for keeping pigs. Rungwe district has about 44,334 pigs which also contribute significantly to the household's economy and nutrition.

Studies in several African countries, provides a rough sense of the likely economics of introducing biodigesters (Schwengels, 2009) where 2 cows or 1 cow and other livestock like pigs can be appropriate for a family to meet the need of cooking biogas while other research findings suggest that farming households, having 2 (zero-grazed) to 10 cattle or 8 to 40 pigs (or a combination) are enough to produce gas for a household. This means that available number of indoor fed dairy cattle of more than 26,000 and over 44000 pigs, the district can have the capacity of having more than 20000 biodigester, this is about 27% of the district's households.

However, despite the high level of indoor fed dairy cattle in Rungwe District and the potential to generate biogas as well as the efforts to promote biogas use in the country since 1970s by the government and donors, biogas technology has not well developed in the district to date. The trend of biogas technology in the district shows that the technology started in 1993 when one person adopted installed a biogas plant (Mwakaje, 2008). In 1996, 12 households got the service by contributing half of the cost. This was a pilot project by the Danish Volunteers that intended to raise awareness of the technology. With the exception of the year 1996, adoption of the biogas technology has remained low and more or less declining (URT, 2005). Up to 2007 there were about 100 biogas plants, an equivalent to only 0.13% of the total households in the district. This is even more surprising as the district has limited fuelwood sources as well as other clean energy sources. Available information shows that the district has a demand of cooking energy of 600,000 m3 per annum, while the capability to supply is about 400,000 m3 (URT, 2005), a 33% deficit (Mwakaje, 2008). The scarcity of fuelwood has increased its cost in terms of purchasing price and time used for fetching (Mwakaje, 2008). The use of other clean energy like electricity and solar power is limited due to both cost and reliability (Mwakaje, 2008).

Why the pace of biogas adoption and use in the district has remained stagnant is the main interest of this study. Although, a study by Mwakaje (2008) highlighted some of the constraining factors, it was not exhaustive. The study focused more on the environmental benefits of adopting biogas technology while other equally important issues related to biogas use and adoption such as socio-economic, institutions; awareness as well as policies were not adequately explained. The main objective of the chapter was to come up with an understanding of the reasons for the stagnated biogas use in Rungwe district despite the availability of large number of dairy cattle and other livestock and in an area with highly inadequate fuelwood supply. Specifically, the chapter investigated issues relates to investment costs, expertise availability, role of institutions and policies in influencing biogas use and level of awareness of biogas use among the Rungwe dwellers. Findings from this study will add to the body of knowledge, inform policy makers, donors, service providers, environmentalists and researchers.

#### **3. Methods**

Data were collected from both primary and secondary sources. Secondary data were collected through literature review using published documents and internet material. There was also a review of policies related to energy in Tanzania. Secondary data helped to establish what has been done in the subject and to read what were the remained gaps for field work were. Institutions supporting biogas development were consulted for

The district is also famous for keeping pigs. Rungwe district has about 44,334 pigs which

Studies in several African countries, provides a rough sense of the likely economics of introducing biodigesters (Schwengels, 2009) where 2 cows or 1 cow and other livestock like pigs can be appropriate for a family to meet the need of cooking biogas while other research findings suggest that farming households, having 2 (zero-grazed) to 10 cattle or 8 to 40 pigs (or a combination) are enough to produce gas for a household. This means that available number of indoor fed dairy cattle of more than 26,000 and over 44000 pigs, the district can have the capacity of having more than 20000 biodigester, this is about 27% of the

However, despite the high level of indoor fed dairy cattle in Rungwe District and the potential to generate biogas as well as the efforts to promote biogas use in the country since 1970s by the government and donors, biogas technology has not well developed in the district to date. The trend of biogas technology in the district shows that the technology started in 1993 when one person adopted installed a biogas plant (Mwakaje, 2008). In 1996, 12 households got the service by contributing half of the cost. This was a pilot project by the Danish Volunteers that intended to raise awareness of the technology. With the exception of the year 1996, adoption of the biogas technology has remained low and more or less declining (URT, 2005). Up to 2007 there were about 100 biogas plants, an equivalent to only 0.13% of the total households in the district. This is even more surprising as the district has limited fuelwood sources as well as other clean energy sources. Available information shows that the district has a demand of cooking energy of 600,000 m3 per annum, while the capability to supply is about 400,000 m3 (URT, 2005), a 33% deficit (Mwakaje, 2008). The scarcity of fuelwood has increased its cost in terms of purchasing price and time used for fetching (Mwakaje, 2008). The use of other clean energy like electricity and solar power is

Why the pace of biogas adoption and use in the district has remained stagnant is the main interest of this study. Although, a study by Mwakaje (2008) highlighted some of the constraining factors, it was not exhaustive. The study focused more on the environmental benefits of adopting biogas technology while other equally important issues related to biogas use and adoption such as socio-economic, institutions; awareness as well as policies were not adequately explained. The main objective of the chapter was to come up with an understanding of the reasons for the stagnated biogas use in Rungwe district despite the availability of large number of dairy cattle and other livestock and in an area with highly inadequate fuelwood supply. Specifically, the chapter investigated issues relates to investment costs, expertise availability, role of institutions and policies in influencing biogas use and level of awareness of biogas use among the Rungwe dwellers. Findings from this study will add to the body of knowledge, inform policy makers, donors, service providers,

Data were collected from both primary and secondary sources. Secondary data were collected through literature review using published documents and internet material. There was also a review of policies related to energy in Tanzania. Secondary data helped to establish what has been done in the subject and to read what were the remained gaps for field work were. Institutions supporting biogas development were consulted for

also contribute significantly to the household's economy and nutrition.

limited due to both cost and reliability (Mwakaje, 2008).

environmentalists and researchers.

**3. Methods** 

district's households.

understanding their performance and constraining factors they are facing. Primary data were collected in areas related to investment cost, awareness, household energy demand, technology service providers, and expertise. In addition, there were consultations with service providers to get information on cost, demand as well as factors constraining the spread of the biogas technology in the District. Furthermore, there was a consultation with local and district institutions and authorities for detailed information on biogas use in the district and whether there has been any efforts to facilitate the adoption of biogas.

The sample frame for this study involved respondents with dairy cattle/biogas use and those with dairy cattle but have not installed biogas plants. Also respondents with access to electricity and other clean energy sources such as LPG were included in the sample. A total of 3 villages were selected for the household sample. These were *Isagilo*, *Kyimo* and *Mpandapanda*. The selection of the villages based on the availability of dairy cows, adoption of biogas technology, availability of other energy sources, socio-economic status and accessibility. The households were selected purposively for those with biogas as well as those with access to electricity as they are few but random for the rest of the dairy keepers.

The total number of households (n) to be surveyed was estimated using the formula below:

$$\text{In} = \frac{\text{N}}{\text{1} + \text{Ne}^2} \tag{1}$$


A sample size of about 10% was selected making a total sample of 120 households. Out of this, 35 had biogas facilities and the remaining 85 had dairy cattle without biogas facility (Table 1). Village roster were used to select the sample households. Data were collected using structured and semi-structured questionnaires and analysed using Statistical Package for Social Sciences (SPSS) as well as livelihoods models. Results have been presented in tables and figures.


Table 1. Village Characteristics and Sample Size (households)

Dairy Farming and the Stagnated Biogas

Education

Table 3. Characteristics of the respondents

**4.2 Characteristics of the respondents by wealth ranks** 

factors preventing the diffusion of biogas technology (Taşdemiroǧlu 1988).

hard time recognizing that their children are not learning much (Banerjee, 2007).

(2007) observation that family size is large for the extremely poor respondents.

Regarding family size respondents from *slightly well off* had small family size (3.3 persons) compared to the *less poor* (4.6 persons) and the *poor* (5.9 persons) (Table 3). This could be explained partly by the low levels of education of the poor. The less educated are more likely to start family life early than educated ones and therefore have high chances of having several children in their reproductive life time. These findings are consistent with Banerjee

Wealth Category *Slightly Well-off Less Poor The Poor* 

Family size (persons) 3.3 4.6 5.9

Married respondents (%) 78.9 82.6 87.9

Female respondents (%) 22.4 40.7 35.7

Respondent's age (years) 48.4 53.5 44.0

No formal education (%) 0 1.3 5.1

Completed primary education (%) 50 59.8 66.7

Completed secondary education (%) 33.3 25.5 20.5

Use in Rungwe District, Tanzania: An Investigation of the Constraining Factors 317

The empirical evidence suggest that the probability of a household adopting biogas technology increases with decreasing age of the head of household, increasing household income, increasing number of cattle owned, increasing household size, male head of household and increasing cost of traditional fuels (Walekhwa et al., 2009). Also economics, material shortage, operation, and the people's acceptance are considered to be the main

Findings on education show the *slightly well-off* respondents to had relatively good education than other categories although the post secondary education was generally low across the three categories. Post secondary education such as vocational and other training is important as it creates professionals and experts including biogas experts in rural areas. The extremely poor spend very little in education hovering around 2% of household budgets (Banerjee (2007). The reason for low spending in education is that children in poor households typically attend public schools or other schools that do not charge a fee even if the education quality is poor. Poor parents are not reacting to the low quality of these schools, either by sending their children to better and more expensive schools or by putting pressure on the government to do something about quality in government schools. This partly occurs because quite often they are illiterate themselves and therefore may have a
